cleverhans | adversarial example library for constructing attacks | Machine Learning library

I'm trying to install and import MDAnalysis and MDAnalysisTests libraries on Google Colaboratory, I've tried three ways but nothing works:

1. Using default: !pip install library

I'm trying to use the Elastic-Net algorithm implemented in Cleverhans to generate adversarial samples in a classification task. The main problem is that i'm trying to use it in a way to obtain an higher confidence at classification time on a target class (different from the original one) but i'm not able to reach good results. The system that i'm trying to fool is a DNN with a softmax output on 10 classes.

For instance:

1. Given a sample of class 3 i want to generate an adversarial sample of class 0.
2. Using the default hyperparameters implemented in the ElasticNetMethod of cleverhans i'm able to obtain a succesful attack, so the class assigned to the adversarial sample became the class 0, but the confidence is quite low(about 30%). This also happens trying different values for the hyperparameters.
3. My purpose is to obtain a quite higher confidence (at least 90%).
4. For other algorithm like "FGSM" or "MadryEtAl" i'm able to reach this purpose creating a loop in which the algorithm is applied until the sample is classified as the target class with a confidence greater than 90%, but i can't to apply this iteration on the EAD algorithm because at each step of the iteration it yields the adversarial sample generated at the first step, and in the following iterations it remains unchanged. (I know that this may happens because the algorithm is different from the other two metioned, but i'm trying to find a solution to reach my purpose).

This is the code that i'm actually using to generate adversarial samples.